Automated pancreatic cyst screening using natural language processing: a new tool in the early detection of pancreatic cancer.

Journal: HPB : the official journal of the International Hepato Pancreato Biliary Association
Published Date: Dec 24, 2014

Abstract

INTRODUCTION: As many as 3% of computed tomography (CT) scans detect pancreatic cysts. Because pancreatic cysts are incidental, ubiquitous and poorly understood, follow-up is often not performed. Pancreatic cysts may have a significant malignant potential and their identification represents a 'window of opportunity' for the early detection of pancreatic cancer. The purpose of this study was to implement an automated Natural Language Processing (NLP)-based pancreatic cyst identification system.

Authors

  • Alexandra M Roch
    Department of Surgery, Indiana University, Indianapolis, IN.
  • Saeed Mehrabi
    Secure Exchange Solution, Rockville, MD.
  • Anand Krishnan
    Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi, India.
  • Heidi E Schmidt
  • Joseph Kesterson
  • Chris Beesley
    Regenstrief Institute Inc., Indianapolis, IN.
  • Paul R Dexter
  • Mathew Palakal
    School of Informatics and Computing, Indiana University, Indianapolis, IN.
  • C Max Schmidt

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